计算机视觉中的结构化学习与预测

IF 3.8 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Foundations and Trends in Computer Graphics and Vision Pub Date : 2011-05-10 DOI:10.1561/0600000033
Sebastian Nowozin, Christoph H. Lampert
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引用次数: 358

摘要

强大的统计模型可以有效地从大量数据中学习,目前正在彻底改变计算机视觉。这些模型具有丰富的内部结构,反映了特定于任务的关系和约束。这本专著向读者介绍了计算机视觉中最流行的结构化模型。我们的重点是离散无向图形模型,我们详细介绍了概率推理和最大后验推理的算法描述。我们单独讨论了最近在一般结构化模型中成功的预测技术。在本专著的第二部分,我们描述了参数学习的方法,其中我们区分了经典的基于极大似然的方法和最近的基于预测的参数学习方法。我们强调了增强当前模型的发展,并讨论了核化模型和潜在变量模型。为了使本专著更加实用,并为进一步的研究提供链接,我们提供了许多方法在计算机视觉文献中成功应用的例子。
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Structured Learning and Prediction in Computer Vision
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structure reflecting task-specific relations and constraints. This monograph introduces the reader to the most popular classes of structured models in computer vision. Our focus is discrete undirected graphical models which we cover in detail together with a description of algorithms for both probabilistic inference and maximum a posteriori inference. We discuss separately recently successful techniques for prediction in general structured models. In the second part of this monograph we describe methods for parameter learning where we distinguish the classic maximum likelihood based methods from the more recent prediction-based parameter learning methods. We highlight developments to enhance current models and discuss kernelized models and latent variable models. To make the monograph more practical and to provide links to further study we provide examples of successful application of many methods in the computer vision literature.
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来源期刊
Foundations and Trends in Computer Graphics and Vision
Foundations and Trends in Computer Graphics and Vision COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
31.20
自引率
0.00%
发文量
1
期刊介绍: The growth in all aspects of research in the last decade has led to a multitude of new publications and an exponential increase in published research. Finding a way through the excellent existing literature and keeping up to date has become a major time-consuming problem. Electronic publishing has given researchers instant access to more articles than ever before. But which articles are the essential ones that should be read to understand and keep abreast with developments of any topic? To address this problem Foundations and Trends® in Computer Graphics and Vision publishes high-quality survey and tutorial monographs of the field. Each issue of Foundations and Trends® in Computer Graphics and Vision comprises a 50-100 page monograph written by research leaders in the field. Monographs that give tutorial coverage of subjects, research retrospectives as well as survey papers that offer state-of-the-art reviews fall within the scope of the journal.
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